Development of a Cost‐Effective Wireless Vibration Weigh‐In‐Motion System to Estimate Axle Weights of Trucks

Wang

et al. 2019

Sensors

In order to control the adverse effect of vehicles overloading infrastructure and traffic safety, weight-in-motion (WIM)-related research has drawn growing attention. To address the high cost of current piezoelectric sensors in installation and maintenance, a study on developing a low-cost piezoceramic sensing system is presented in this paper. The proposed system features distributed monitoring and integrated packaging, for calculating vehicle’s dynamic load and its wheel position. Results from the laboratory tests show that the total output of the sensing system increases linearly with the increase of the peak load when the loading amplitude is 5–25 kN (equivalent to the half-axis load of 20–100 kN); when the loading frequency is between 15 Hz and 19 Hz (equivalent to a speed of 17.8–23.2 km/h), the total output of the system fluctuates around a value of 1.305 V. Combined with finite-element simulation, the system can locate load lateral position with a resolution of 120 mm. Due to the protection packaging, the peak load transferred to the sensing units is approximately 4.36% of the applied peak load. The study indicates the proposed system can provide a promising low-cost, reliable and practical alternative for current WIM systems.

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development of a Novel Piezoelectric Sensing System for Pavement Dynamic Load Identification

Wang

et al. 2019

Sensors

“…Thus, it is of practical significance to develop a better FEQS system that is free of human labor, low cost, and well-adapted to the operating environment. Currently, there is no suitable solution for non-contact truck weighing; although devices that are more advanced than scales have been developed, contact with vehicles and laborious installation are still required [18,19]. Thus, high cost and limited application is unavoidable in weighing FEQS.…”

Section: Needs For Vision-based Feqs Methodsmentioning

confidence: 99%

Deep Learning Model Comparison for Vision-Based Classification of Full/Empty-Load Trucks in Earthmoving Operations

et al. 2019

Earthmoving is an integral civil engineering operation of significance, and tracking its productivity requires the statistics of loads moved by dump trucks. Since current truck loads’ statistics methods are laborious, costly, and limited in application, this paper presents the framework of a novel, automated, non-contact field earthmoving quantity statistics (FEQS) for projects with large earthmoving demands that use uniform and uncovered trucks. The proposed FEQS framework utilizes field surveillance systems and adopts vision-based deep learning for full/empty-load truck classification as the core work. Since convolutional neural network (CNN) and its transfer learning (TL) forms are popular vision-based deep learning models and numerous in type, a comparison study is conducted to test the framework’s core work feasibility and evaluate the performance of different deep learning models in implementation. The comparison study involved 12 CNN or CNN-TL models in full/empty-load truck classification, and the results revealed that while several provided satisfactory performance, the VGG16-FineTune provided the optimal performance. This proved the core work feasibility of the proposed FEQS framework. Further discussion provides model choice suggestions that CNN-TL models are more feasible than CNN prototypes, and models that adopt different TL methods have advantages in either working accuracy or speed for different tasks.

“…In some applications, if the net acceleration or force acting on the system over the entire time range is gravity, an accelerometer can be used to measure the static angle of the tilt [15]. For tilt monitoring with accelerometers, gravity is assumed to be the only acceleration stimulus.…”

Section: Principles Of Wireless Monitoring Technology For Undergroundmentioning

confidence: 99%

Mathematical Modeling and Numerical Analysis of Force Monitoring of Foundation Pit Support Structure Based on Vibration Response Sensor System

2019

IJOMAM

In order to study the stability and safety of the foundation pit supporting structure system, the wireless tilting vibration sensor is used to discuss the underground monitoring of the underground engineering, the horizontal displacement monitoring of the foundation pit support and the deep foundation pit supporting structure. The actual measured data is compared with the mathematical simulation values. The results show that the foundation pit engineering and shield tunnel engineering can use the wireless vibration tilt sensor for underground engineering monitoring. The width of the foundation pit and the way of excavation are the main factors affecting the internal force and stability of the steel support. With the layered excavation of the foundation pit, the deformation of the retaining structure also has obvious segmental features. The subsection excavation according to the space-time effect can effectively reduce the lateral displacement of the retaining structure. Therefore, for the structural characteristics of underground engineering, the wireless vibration tilt sensor and the method of finite element numerical simulation are combined. The joint support system of steel support and retaining pile has a coordination relationship between deformation and force. The steel support can effectively control the deformation of the envelope structure. When the steel support is erected and 60% of the design axial force value is added, the deformation of the retaining structure can be better reduced. Furthermore, the safety and stability of the structure is increased.